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Pavlo Maruschak, Ihor Konovalenko, Yaroslav Osadtsa, Volodymyr Medvid, Oleksandr Shovkun, Denys Baran, Halyna Kozbur and Roman Mykhailyshyn
Modern neural networks have made great strides in recognising objects in images and are widely used in defect detection. However, the output of a neural network strongly depends on both the training dataset and the conditions under which the image was ac...
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Omar Abdulkhaleq Aldabash and Mehmet Fatih Akay
An IDS (Intrusion Detection System) is essential for network security experts, as it allows one to identify and respond to abnormal traffic present in a network. An IDS can be utilized for evaluating the various types of malicious attacks. Hence, detecti...
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Max Schrötter, Andreas Niemann and Bettina Schnor
Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusi...
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Jui-Fa Chen, Yu-Ting Liao and Po-Chun Wang
Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, tra...
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